SESAR: The Past, Present, and Future of European Air Traffic Management Research

The Single European Sky ATM Research (SESAR) project is the technological pillar of the European Commission’s Single European Sky Initiative to modernize air traffic management (ATM). Here, we describe the process of establishing SESAR and the main parts of the project: the research and development (R&D) part, which is led by the SESAR Joint Undertaking; the deployment part, which is managed by the SESAR Deployment Manager; and the European ATM Master Plan, which collects and lays out both the R&D and deployment needs. The latest European ATM Master Plan was adopted just prior to the current pandemic. The huge loss in air traffic due to the pandemic, and the speed of the recovery of the aviation industry will require reprioritization, but the main elements that have been established—particularly those in support of the environment—remain valid

D6.1 Intermediate concept assessment report

This Technical Report presents an interim synthesis of the stakeholders' input and the specifications stemming from internal discussions and the stakeholder workshop. It presents the main issues related to the concepts attached to the mechanisms selected in D3.1, for instance in terms of market mechanism design. Following the output of these discussions, some specifications for the project, and sometimes for the models, are laid out

Engage D3.1 Final workshop presentations of wave 1 catalyst-funded projects

This deliverable collates the final presentations of catalyst-funded wave 1 projects, given at Engage thematic challenge workshops

NOSTROMO: Lessons learned, conclusions and way forward

This White Paper sets out to explain the value that metamodelling can bring to air traffic management (ATM) research. It will define metamodelling and explore what it can, and cannot, do. The reader is assumed to have basic knowledge of SESAR: the Single European Sky ATM Research project. An important element of SESAR, as the technological pillar of the Single European Sky initiative, is to bring about improvements, as measured through specific key performance indicators (KPIs), and as implemented by a series of so-called SESAR 'Solutions'. These 'Solutions' are new or improved operational procedures or technologies, designed to meet operational and performance improvements described in the European ATM Master Plan

Engage D3.2 Final workshop presentations of wave 2 catalyst-funded projects

This deliverable collates the final presentations of catalyst-funded wave 2 projects, given at Engage thematic challenge workshops and associated events

Green-GEAR

The poster describes the approach of the Green-GEAR project that kicked off in September. Green-GEAR tackles three environmental inefficiencies. First (solution 1), barometric altimetry – used since the early days of aviation – suffers from constant variations in pressure caused by the weather, leading to increased vertical profile variability restricting capacity and flight efficiency in today’s high traffic density. Green-GEAR will thus investigate the environmental potential of geometric altimetry enabled by satellite navigation. Second (solution 2), geometric altimetry is an enabler for the integration of new entrants such as RPAS and HAO aircraft, and its increased accuracy is expected to allow reduction of vertical separation en-route (allowing more aircraft to fly at their optimum altitude), which will be analysed in the project. Finally (solution 3), the project will investigate the potential of new route-charging mechanisms that incentivise miminimum climate impact routing

Engage D2.7 Annual combined thematic workshops progress report

This deliverable reports on the organisation and results obtained from the third and fourth editions of the Engage thematic challenge (TC) workshops held in 2021. Due to the Covid-19 pandemic, the third editions of the TC2 and TC3 workshops, initially scheduled to be held in 2020, were delayed to the beginning of 2021. The TC1 and TC4 workshops reached their third edition in 2021, while TC2 and TC3 closed with the fourth edition. The main lessons learned relate to data availability, collaboration opportunities, machine learning and artificial intelligence methodologies and approaches, and incentives for future ATM implementations

Capacity sharing within Virtual Centre: How much delay can be reduced?

Airspace Architecture Study proposed the future Single European Airspace System, based on modern technologies that could divide the air traffic service provision from local infrastructure for data provision, enabling the decoupling of geographical location from the service provision. This decoupling would enable virtualisation where service providers could use data from the common data services, opening doors to different organisation of air traffic service provision, namely more advanced capacity sharing. Virtualisation concept is still under development and several recent studies evaluated some aspects of virtualisation in ATM, but did not yet address in detail the impacts of different Virtual Centre implementation scenarios. In this paper, we propose a linear optimisation model to evaluate the impact of virtualisation and capacity sharing in terms of delay reduction. We show that taking into account the current airspace design and air traffic management resources, even the air navigation service providers that accumulate the highest capacity-caused delays could decrease those in the range of 25-50% up to about 80% through internal collaboration. Furthermore, the decrease of over 50% of the total capacity caused delays could be obtained if FABEC1 were to form a Virtual Centre, and the decrease of about 90% of the total European delay if the Single European Sky (SES) area would form a Virtual Centre. The analysed capacity sharing collaborations indicate the possibility of significant delay reductions, but would not be sufficient, on their own, to eliminate capacity-caused issues in Europe

New mathematical model for extended arrival management capabilities

The Extended arrival management (E-AMAN) concept is based on starting the arrival traffic sequencing earlier than is the case by the arrival management (AMAN). The E-AMAN extends the horizon at which to start sequencing from the airport terminal area further upstream, to enable more smooth traffic management through speeding up, or slowing down arriving flights. Current application of E-AMAN at Heathrow, with the horizon at 350NM reduces delay, operational costs, CO2 emission and smooths delivery of arrival traffic to the runways. Here we propose an E-AMAN model that extends to 500NM. More specifically, the model incorporates three horizons: Tactical Horizon (100NM), Command Horizon (500NM), and Data Horizon (600NM). When a flight enters Data Horizon, the flight intentions are sent to the E-AMAN. When a flight enters Command Horizon, the optimizer is run to find optimal slot for that flight at the runway. Compared to previous optimisation processes, the E-AMAN takes into account the cost of delay and fuel for the airline instead of delay alone, and uses information on the distribution time of arrival to manage uncertainty (e.g. due to wind). Based on the optimal slot assigned, the E-AMAN issues a command to the flight, that can be to maintain initial speed, to speed up, or to slow down. It also assigns minutes of holding if delay cannot be absorbed during cruise. We will present some evidence of the efficiency of the optimisation process, in particular compared to a baseline scenario where the E-AMAN takes only delay into account and no uncertainty. We will show how this efficiency changes in different conditions, in particular relative to wind uncertainty

Estimating economic severity of Air Traffic Flow Management regulations

The development of trajectory-based operations and the rolling network operations plan in European air traffic management network implies a move towards more collaborative, strategic flight planning. This opens up the possibility for inclusion of additional information in the collaborative decision-making process. With that in mind, we define the indicator for the economic risk of network elements (e.g., sectors or airports) as the expected costs that the elements impose on airspace users due to Air Traffic Flow Management (ATFM) regulations. The definition of the indicator is based on the analysis of historical ATFM regulations data, that provides an indication of the risk of accruing delay. This risk of delay is translated into a monetary risk for the airspace users, creating the new metric of the economic risk of a given airspace element. We then use some machine learning techniques to find the parameters leading to this economic risk. The metric is accompanied by an indication of the accuracy of the delay–cost prediction model. Lastly, the economic risk is transformed into a qualitative economic severity classification. The economic risks and consequently economic severity can be estimated for different temporal horizons and time periods providing an indicator which can be used by Air Navigation Service Providers to identify areas which might need the implementation of strategic measures (e.g., resectorisation or capacity provision change), and by Airspace Users to consider operation of routes which use specific airspace regions